Method and Device for Encoding a Sequence of Images and Method and Device for Decoding a Sequence of Images

ABSTRACT

A method and device for deriving at least one motion information predictor for encoding of an image portion by motion compensation. At least two distinct first and second subsets of motion information predictors of a first set of motion information predictors are provided. Processing of the first subset of motion information predictors and processing of the second subset of motion information predictors is performed to obtain a final set of motion information predictors usable for predicting said image portion from the reference image portion. Processing of the second subset may comprise removing duplicates from among the motion information predictors of said second subset, and may be performed so as to exclude temporal predictors. At least part of the processing of the second subset of motion information predictors may be performed concurrently with at least part of the processing of the first subset of motion information predictors.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. patent application No.U.S. patent application Ser. No. 16/985,078, filed on Aug. 4, 2020,which is a continuation of Ser. No. 16/352,625, filed on Mar. 13, 2019and issued as U.S. Pat. No. 10,771,806 on Sep. 8, 2020, which is acontinuation of U.S. patent application Ser. No. 14/238,821, filed onFeb. 13, 2014 and issued as U.S. Pat. No. 10,306,256 on May 28, 2019,which is a National Stage Entry of PCT/EP2012/003490, filed Aug. 16,2012 and claims priority from Great Britain Patent Application No.1114184.3 filed Aug. 17, 2011, all of which are hereby incorporated byreference herein in their entirety.

The present invention concerns a method and device for encoding asequence of digital images and a method and device for decoding acorresponding bitstream. The invention further relates to a method anddevice for deriving motion information, including at least one motioninformation predictor for predicting an image portion of an imagepredicted by motion compensation with respect to at least one referenceimage portion.

The invention may be applied in the field of digital signal processing,and in particular in the field of video compression using motioncompensation to reduce spatial and temporal redundancies in videostreams.

Many video compression formats, such as for example H.263, H.264,MPEG-1, MPEG-2, MPEG-4, SVC, use block-based discrete cosine transform(DCT) and motion compensation to remove spatial and temporalredundancies. They can be referred to as predictive video formats. Eachframe or image of the video signal is divided into slices which areencoded and can be decoded independently. A slice is typically arectangular portion of the frame, or more generally, a portion of aframe or an entire frame. Further, each slice is divided intomacroblocks (MBs), and each macroblock is further divided into blocks,typically blocks of 8×8 pixels. The encoded frames are of two types:temporal predicted frames (either predicted from one reference framecalled P-frames or predicted from two reference frames called B-frames)and non temporal predicted frames (called Intra frames or I-frames).

Temporal prediction consists in finding in a reference frame, either aprevious or a future frame of the video sequence, an image portion orreference area which is the closest to the block to encode. This step istypically known as motion estimation. Next, the block is predicted usingthe reference area in a step typically referred to as motioncompensation—the difference between the block to encode and thereference portion is encoded, along with an item of motion informationrelative to the motion vector which indicates the reference area to usefor motion compensation. In INTRA prediction, a prediction direction isencoded.

In order to further reduce the cost of encoding motion information, amotion vector may be encoded in terms of a difference between the motionvector and a motion vector predictor, typically computed from one ormore motion vectors of the blocks surrounding the block to encode.

In H.264, motion vectors are encoded with respect to a median predictorcomputed from the motion vectors situated in a causal neighbourhood ofthe block to encode, for example from the blocks situated above and tothe left of the block to encode. The difference, also referred to as aresidual motion vector, between the median predictor and the currentblock motion vector is encoded to reduce the encoding cost.

Encoding using residual motion vectors saves some bitrate, butnecessitates that the decoder performs the same computation of themotion vector predictor in order to decode the value of the motionvector of a block to decode.

Recently, further improvements in coding efficiency have been proposed,such as using a plurality of possible motion vector predictors. Thismethod, often referred to as motion vector competition (MVCOMP),consists in determining from among several motion vector predictors orcandidates which motion vector predictor minimizes the encoding cost,typically a rate-distortion cost, of the residual motion information.The residual motion information comprises the residual motion vector,i.e. the difference between the actual motion vector of the block toencode and the selected motion vector predictor, and an item ofinformation indicating the selected motion vector predictor, such as forexample an encoded value of the index of the selected motion vectorpredictor. The index of the selected motion vector predictor is coded inthe bitstream with a unary max code based on a fixed list size.

In High Efficiency Video Coding (HEVC), a new implementation of the sameconcept for enabling the selection of the best predictor, from a givenset of predictors composed of spatial motion vectors and temporal motionvectors, has been proposed. This technique is referred to as AdvancedMotion Vector Prediction (AMVP). If some predictors from among thesepredictors of the given set are duplicates of other predictors in theset, the duplicates can be removed and further predictors can be addedto the set to create a new second set of predictors. The addedpredictors can be a combination of the spatial and temporal predictorsalready in the set, other predictors derived form these spatial andtemporal predictors, or predictors with fixed values. Finally, theduplicate predictors of the second set of predictors are removed inorder to obtain non-redundant candidates in the second set ofpredictors.

The generated second set of predictors significantly increases thecomputational complexity of the derivation process. The increasedcomputational complexity results from the cascade predictors generation.

The current HEVC implementation uses a set of motion vector predictorscontaining at most 2 predictors for the Inter mode and at most 5predictors for the Merge Skip mode and the Merge mode.

In the current HEVC design, Inter prediction can be unidirectional orbi-directional. Uni-directional refers to one predictor block being usedto predict the current block. The one predictor block is defined by alist index, a reference frame index and a motion vector. The list indexcorresponds to a list of reference frames. It may be considered, forexample, that two lists are used: L0 and L1. One list contains at leastone reference frame and a reference frame can be included in both lists.A motion vector has two components: horizontal and vertical. The motionvector corresponds to the spatial displacement in term of pixels betweenthe current block and the temporal predictor block in the referenceframe. Thus, the block predictor for the uni-directional prediction isthe block from the reference frame (ref index) of the list, pointed toby the motion vector.

For Bi-directional Inter prediction two block predictors are considered.One for each list (L0 and L1). Consequently, 2 reference frame indexesare considered as well as 2 motion vectors. The Inter block predictorfor bi-prediction is the average, pixel by pixel, of the two blockspointed to by these two motion vectors.

The motion information dedicated to the Inter block predictor can bedefined by the following parameters:

-   -   Direction type: uni or bi    -   One list (uni-direction) or two lists (bi-direction): L0, L1, L0        and L1.    -   One (uni-direction) or two reference frame indexes        (bi-direction): RefL0, RefL1, (RefL0, RefL1).    -   One (uni-direction) or two (bi-direction) motion vectors: each        motion vector has two components (horizontal mvx and vertical        mvy).

It may be noted that the bi-directional Inter predictor may only be usedfor a B type slice type. Inter prediction in B slices can be uni orbi-directional. In P slices, the Inter prediction is onlyuni-directional.

The current design of HEVC uses 3 different Inter modes: an Inter mode,a Merge mode and a Merge Skip mode. The main difference between thesemodes is the data signaling in the bitstream.

In the Inter mode all data are explicitly signaled. This means that thetexture residual is coded and inserted into the bitstream (the textureresidual is the difference between the current block and the Interprediction block). For the motion information, all data are coded. Thus,the direction type is coded (uni or bi-directional). The list index, ifneeded, is also coded and inserted into the bitstream. The relatedreference frame indexes are explicitly coded and inserted into thebitstream. The motion vector value is predicted by the selected motionvector predictor. The motion vector residual for each component is thencoded and inserted into the bitstream followed by the predictor index.

In the Merge mode, the texture residual and the predictor index arecoded and inserted into the bitstream. A motion vector residual,direction type, list or reference frame index are not coded. Thesemotion parameters are derived from the predictor index. Thus, thepredictor is the predictor of all data of the motion information.

In the Merge Skip mode no information is transmitted to the decoder sideexcept for the “mode” and the predictor index. In this mode theprocessing is similar to the Merge mode except that no texture residualis coded or transmitted. The pixel values of a Merge Skip block are thepixel values of the block predictor.

In the set of motion information predictors represented in FIG. 1, twospatial motion vectors of the Inter mode are chosen from among thoseblocks, in Frame N, which are above and to the left of the block to beencoded, including the above corner blocks and left corner block.

The left predictor is selected from among the blocks “Below Left” and“Left”. The following conditions are evaluated in the specified orderuntil a motion vector value is found:

1. The motion vector from the same reference list and the same referencepicture

2. The motion vector from the other reference list and the samereference picture

3. The scaled motion vector from the same reference list and a differentreference picture

4. The scaled motion vector from the other reference list and adifferent reference picture

If no value is found, the left predictor is considered as beingunavailable. In this case, it indicates that the related blocks wereIntra coded or those blocks do not exist. The above predictor isselected from among “Above Right”, “Above” and “Above left” in thisspecific order, with the same conditions as described above.

The temporal motion predictor comes from the nearest reference frame inlow delay configuration. In the case of B frames, 2 motion vectors areconsidered for the collocated block in frame N−1. One is in the firstlist “L0” and one is in the second list “L1”. If both motion vectorsexist, the motion vector which has the shortest temporal distance isselected. If both motion vector predictors have the same temporaldistance, the motion from the first list “L0” is selected. Thecollocated motion vector selected is then scaled, if needed, accordingto its temporal distance and to the temporal distance of the encodedmotion vector. If no collocated predictor exists, the predictor isconsidered as unavailable.

For hierarchical B frames coding, 2 collocated motion vectors can beconsidered. Both come from the future reference frame. The motion vectorwhich crosses the current frame is selected. If both predictors crossthe current frame, the motion vector which has the shortest temporaldistance is selected. If both predictors have the same temporaldistance, the motion from the first list “L0” is then selected. Thecollocated motion vector selected is then scaled, if needed, accordingto its temporal distance and to the temporal distance of the encodedmotion vector. If no collocated predictor exists, the predictor isconsidered as unavailable.

For the low delay case and hierarchical case, when the collocated blockis divided into a plurality of partitions (potentially, the collocatedblock contains a plurality of motion vectors), the partition selected isthe top left center partition. Moreover, the temporal predictor is themotion vector of the block at the bottom right position of thecollocated block (position H in FIG. 1). If this block does not exist orif it is Intra coded, the block at the center position of the collocatedblock is selected as the motion vector which will be derived.

The motion predictor value is then added to the set of predictors.

Finally, the suppression process is applied. This consists in removingduplicate predictors from the set of selected motion vector predictors.At the end of this process, the set contains non-duplicate motion vectorpredictors. This set can contain 1, 2, 3 or 4 predictors. In the currentdesign, the list of predictors is fixed in order to limit the list sizeto 2. Consequently, the selected predictor is coded with one bit. Thus,if the number of predictors in the list is 3 or 4, the last predictor orrespectively the 2 last predictors are removed.

A predictor of merge modes (“classical” or Skip) represents all themotion information: direction, list, reference frame index and motionvectors. The predictor index is coded with a unary max code as depictedin Table 1.

TABLE 1 Codeword when the amount of predictors in the set is N Index N=1N=2 N=3 N=4 N=5 0 (inferred) 0 0 0 0 1 1 10 10 10 2 11 110 110 3 1111110 4 1111

The list size is fixed to 5 for all Merge blocks or Merge Skip blocks inthe current HEVC design.

FIG. 2 is a flow chart of an example of a motion vector derivationprocess for Merge Modes of Interprediction (Merge Skip and Merge havethe same motion vector predictor derivation process). The method isapplied to obtain a set of potential motion information predictors forencoding of an image portion of an image with respect to a referenceimage portion. In the first step of the derivation, 7 block positionsare considered (601 to 607). These positions are the spatial andtemporal positions depicted in FIG. 1 (each position is labeled the sameis both figures). Module 608 checks the availability of these motionvectors and selects at most 5 motion vectors. This module implementingstep 608 determines that a predictor is available if it exists and ifthe block is not Intra coded. The selection and the verification of the5 selected motion vectors is executed in accordance with the followingconditions:

-   -   If the “Left” motion vector (601) is available (i.e. if it        exists and if this block is not Intra coded), the motion vector        of the “Left” block is selected and used as the predictor 1        (610).    -   If the “Above” motion vector (602) is available, the motion        vector of the “Above” block is selected and used as the        predictor 2 (611).    -   If the “Above Right” motion vector (603) is available, the        motion vector of the “Above Right” block is selected and used as        the predictor 3 (612).    -   If the “Below Left” motion vector (604) is available, the motion        vector of the “Below Left” block is selected and used as the        predictor 4 (613).    -   If one (or more) of the preceding predictors is not available        and if the “Above Left” motion vector (605) is available, the        motion vector of the “Above Left” block is added to the set of        motion vector predictors after the added spatial predictor.    -   If the “H” motion vector is available, the motion vector of the        “H” block is selected and used as the predictor 5 (614). If the        “H” block is not available, the availability of the “collocated”        motion vector (i.e. the motion vector of the block at the same        position in the reference frame as the current block in the        current frame) is checked and, if it exists, it is used as the        temporal predictor. The availability check performed by the        module 608 requires 1 cycle.

The temporal predictor should be scaled if needed. Indeed, for thetemporal motion vector, the direction and the reference frame index donot depend on the H or collocated block but on the data of the currentslice. If the current block is in a B slice, the temporal predictor isalways bidirectional and always unidirectional for P slices. Thereference frame indexes for each list of reference frames (L0, L1) arederived from the Left and the Above predictor. If, for a list, both theLeft and Above blocks have no reference frame index, the reference frameindex for the temporal predictor is set to zero.

Since the reference frame index for the temporal predictor does notdepend on the reference frame index of the “H” or “collocated” block buton the reference frame of the Left and Above predictor, its motionvector value should be scaled. This means that if the temporal distancecovered by the temporal motion vector is different to the differencebetween the current frame and the reference frame of the predictor, thetemporal motion vector is scaled to cover the correct temporal distance.

At the end of the modules 608 and 609, the predictor set contains atmost 5 predictors (610 to 614). Next, a suppression process 615 isapplied in order to remove duplicate candidates from the predictor set.This process consists in comparing each predictor of the set to all theother predictors in the same set and in removing those predictors whichare equal to another predictor in the set (while keeping the otherpredictor of which the duplicate candidate is a duplicate in the set) sothat there are no duplicates among the predictors in the set. Thesuppression process for P slices takes into account the values of themotion vectors and their reference frame indexes. Accordingly, the twocomponents of a motion vector and its reference index are compared toall the others and only if these three values are equal, is thepredictor removed from the set. For a B frame, this criterion isextended to the direction and the lists. Thus, a predictor is consideredas a duplicate predictor if it uses the same direction, the same lists(L0, L1, or L0 and L1), the reference frame indexes and the same valueof the motion vectors (MV_L0 and MV_L1 for bi prediction). Thesuppression process lasts 1 cycle when 5 predictors at most need to becompared. Indeed, it may be considered that 12 comparisons can becomputed in 1 cycle. The number of comparisons for the suppressionprocess in the most complex case is equal to the Sum of 0 to N−1.Consequently, for 5 predictors 10 comparisons are needed (i.e.4+3+2+1=10).

At the end of this suppression process 615, a reduced predictors set isgenerated 616.

Next, a motion vector generation module 617 generates new candidatesbased on the reduced motion vector predictor set. This processing cantypically last for at least one cycle. It may be noted that in thecurrent HEVC design, the scheme used can produce a maximum of 20predictors in the most complex case. This module 617 produces a secondset of predictors 618.

The second set of predictors 618 is added to the reduced set ofpredictors 616 and the suppression process is applied to remove theduplicate candidates of this second predictor set compared to both thereduced and second sets. This suppression process is similar to thesuppression process of module 615. Yet at the end, if the list containsmore than 5 predictors the list of predictors is truncated to 5 which isthe current list size defined in the HEVC design. It may be noted thatthis process can last at least 1 cycle. However the duration of thecycle depends on the number of predictors generated in the second set ofpredictors 618. In the current implementation of HEVC, this processlasts 3 cycles because of the amount of predictors generated (mostcomplex case: 32 comparisons for the current design).

Finally, the suppression process 619 produces a final list of predictors620 from where the predictor for the current block will be extracted.

A drawback of the process is that the current motion vector predictorderivation for the Merge mode can reach 11 cycles in the most complexcase while at least 5 cycles are needed in the least complex case.Motion vector derivation thus has a significant impact on encoding anddecoding complexity.

The present invention has been devised to address one or more of theforegoing concerns.

According to a first aspect of the invention there is provided a methodof deriving at least one motion information predictor for encoding ordecoding of an image portion of an image by motion compensation withrespect to at least one reference image portion, wherein for said imageportion to be encoded or decoded, the method comprises: providing, forprocessing, at least two distinct first and second subsets of motioninformation predictors of a first set of motion information predictors;processing the first subset of motion information predictors; andprocessing the second subset of motion information predictors, at leastpart of the processing of the second subset of motion informationpredictors being performed concurrently with at least part of theprocessing of the first subset of motion information predictors; andobtaining, based on motion information predictors resulting from theprocessing of the first subset of motion information predictors and theprocessing of the second subset of motion information predictors, afinal set of motion information predictors usable for predicting saidimage portion from the reference image portion.

The computational complexity of the current HEVC design can thus bereduced by processing the motion vector derivation in parallel.

In embodiments of the invention a motion information predictor includesat least a motion vector predictor. In further embodiments a motioninformation predictor may further include motion information parameterssuch as index of the reference image, direction type: uni or bi, Onelist (uni-direction) or two lists (bi-direction): L0, L1, L0 and L1. Insome embodiments each motion vector predictor has two components(horizontal and vertical).

In some embodiments of the invention the first subset comprises at leastone temporal motion information predictor and the second subsetcomprises at least one spatial motion information predictor.

In a particular embodiment of the invention a first subset of motioninformation predictors includes a temporal motion information predictorand processing of the first subset of the first set comprises temporallyscaling the temporal motion information predictor based on the temporaldifference between the image of the image portion to be encoded andimage of the reference image portion.

Processing of the second subset may include generating a set ofnon-duplicate motion information predictors in which there are noduplicates among the motion information predictors of the said set.

In embodiments of the invention a motion information predictor may beconsidered to be a duplicate of another motion information predictor ifthe respective values of the two components of each motion vector andother association motion information parameters are equal to oneanother.

Processing of the second subset may include generating one or moreadditional motion information predictors based on the motion informationpredictors of the second subset. For example, generating one or moreadditional motion information predictors comprises combining one or moremotion information predictors of the second subset, and/or adding anoffset to one or more information predictors of the second subset.

By generating the additional predictors based only on predictors whichdo not need scaling operations complexity is reduced and the scalingprocess may be operated in parallel to the new generation of predictors.The number of cycles needed for the derivation motion vectors of Mergemodes can be reduced and the number of comparisons needed for the Mergemodes motion vector to provide a set of non-duplicate predictors is alsoreduced.

In an embodiment, processing of the second subset of the first set ofmotion information predictors comprises removing duplicates from amongthe motion information predictors of said second subset, in the casewhere the second subset contains one or more motion informationpredictors which are the same, to provide a reduced subset of motioninformation predictors; and generating further motion informationpredictors based on the reduced subset of motion information predictorsto provide a further second subset of motion information predictors.

There may be provided, independently, in a related aspect of theinvention, a method of deriving at least one motion informationpredictor for encoding or decoding of an image portion of an image bymotion compensation with respect to at least one reference imageportion, wherein for said image portion to be encoded or decoded, themethod comprises providing, for processing, at least two distinct firstand second subsets of motion information predictors of a first set ofmotion information predictors (801-807), the first subset comprising atleast one temporal motion information predictor, and the second subsetcomprising at least one spatial motion information predictor andexcluding any temporal motion information predictor; processing (808,809) the first subset of motion information predictors; and processing(808, 815, 817) the second subset of motion information predictors; andobtaining (819), based on motion information predictors (818, 814)resulting from the processing of the first subset of motion informationpredictors and the processing of the second subset of motion informationpredictors, a final set (820) of motion information predictors usablefor predicting said image portion from the reference image portion;wherein the processing of the second subset comprises removingduplicates from among the motion information predictors of said secondsubset only, in the case where the second subset contains one or moremotion information predictors which are the same, to provide a reducedsubset of motion information predictors (816).

Since temporal predictors are excluded from selection for the secondsubset, it will be understood that the process of removing orsuppressing duplicates from among the selected predictors of the secondsubset can be applied to spatial predictors only, and in this way doesnot involve processing temporal motion information predictors.

By excluding temporal predictors from the suppression process in thisway, the overall number of comparisons is reduced, thereby loweringcomputational complexity.

Conversely, in certain embodiments spatial predictors are excluded fromselection for the first subset. Processing of the first set (ie thetemporal motion predictors) may not involve removal of duplicates insome embodiments, although, as explained in greater detail below,embodiments may advantageously combine processed first and secondsubsets so as to exclude duplicates at the stage of obtaining the finalset. Stated differently, processing of the first set may therefore notinvolve removal of duplicates prior to obtaining the final set.

In an embodiment, scaling of the temporal motion information predictorof the first subset is performed concurrently with the steps of removingduplicates and generating further motion information predictors of thesecond subset.

In an embodiment, the method includes: removing duplicates from amongthe motion information predictors resulting from the processing of thefirst subset of motion information predictors and the processing of thesecond subset of motion information predictors, in the case where one ormore motion information predictors resulting from the processing of thefirst subset of motion information predictors and the processing of thesecond subset of motion information predictors are the same, to providethe final set of motion information predictors usable for encoding saidimage portion such that are no duplicates among the final set of motioninformation predictors.

In an embodiment, the processing of the second subset of motioninformation predictors further comprises removing duplicates from amongthe motion information predictors of the further second subset of motioninformation predictors in the case where the further second subsetcontains one or more motion information predictors which are the same,to provide a second reduced subset of motion information predictors.

In an embodiment, the step of removing duplicates from among the motioninformation predictors of the further second subset is performedconcurrently with scaling of the temporal motion information predictorof the first subset.

In an embodiment the method includes adding, to the second reducedsubset of motion information predictors, a motion information predictor,resulting from the processing of the first subset of motion informationpredictors, which is not a duplicate of any of the motion informationpredictors of the second reduced subset of motion information predictorsto obtain the final set of motion information predictors.

In an embodiment, the method includes adding, to the reduced subset ofmotion information predictors, a motion information predictor resultingfrom the processing of the first subset of motion information predictorswhich is not a duplicate of any of the motion information predictors ofthe reduced subset of motion information predictors; and wherein thefinal set of motion information predictors comprises non duplicatemotion vectors from among the motion vector predictors of the reducedsubset of motion information predictors and the further second subset ofmotion information predictors.

In an embodiment, the processing of the second subset performedconcurrently with the processing of the first subset is based on anestimation of the duration of the processing of the first subset.

In an embodiment, the motion information predictors resulting from theprocessing of the second subset which are added to the motioninformation predictors resulting from the processing of the first subsetto obtain the final set of motion information predictors is based on theduration of the processing of the first subset.

In an embodiment, the method includes a step of determining, based onthe temporal difference between the image of the image portion and theimage of the reference image portion, whether or not a temporal scalingprocess is to be applied to the first subset of motion informationpredictors; and wherein in the case where it is determined that atemporal scaling process is to be applied, processing of the firstsubset of motion information predictors comprises a step of temporalscaling the motion information predictors of the first subset of motioninformation predictors based on the temporal difference between theimage of the image portion and the image of the reference image portion;otherwise, in the case where it is determined that a temporal scalingprocess is not to be applied, processing of the first subset of motioninformation predictors comprises a step of removing duplicates fromamong the motion information predictors of the first subset of motioninformation predictors such that a reduced subset comprisingnon-duplicate motion information predictors from among the motioninformation predictors of the first subset of motion informationpredictors and the second subset of motion information predictors isprovided by processing of the first subset of motion informationpredictors and processing of the second subset of motion informationpredictors.

In an embodiment, in the case where it is determined that a temporalscaling process is to be applied, the final set of predictors isobtained by removing duplicates from among the motion informationpredictors resulting from the concurrent processing of the first subsetof motion information predictors and the second subset of motioninformation predictors; otherwise in the case where it is determinedthat a temporal scaling process is not to be applied, the final set ofpredictors is obtained by generating further motion informationpredictors, based on the reduced subset to provide a further secondsubset of motion information predictors and removing duplicates fromamong the further second subset of motion information predictors.

In an embodiment, the method includes determining the complexity of thetemporally scaling process of the first subset of motion informationpredictors and wherein, in the case where it is determined that thetemporal scaling process will last for a longer duration than apredetermined duration threshold, the final set of motion informationpredictors is obtained by removing duplicates from among the motioninformation predictors resulting from the processing of the first subsetof motion information predictors and the processing of the second subsetof motion information predictors; otherwise, in the case where it isdetermined that the temporal scaling process will last for a shorterduration than a predetermined duration threshold, the final set ofpredictors is obtained by adding, to the reduced subset of motioninformation predictors obtained from the second subset of motion vectorpredictors, a motion information predictor resulting from processing ofthe first subset of motion information predictors which is not aduplicate of any of the motion information predictors of the reducedsubset of motion information predictors; wherein the final set of motioninformation predictors comprises non duplicate motion informationpredictors from among the motion information predictors of the reducedsubset of motion information predictors and the further second subset ofmotion information predictors.

In an embodiment, processing of the second subset of the first set ofmotion information predictors comprises removing duplicates from amongthe motion information predictors of said second subset to provide areduced subset of motion information predictors; and generating afurther set of motion information predictors based on one of the motioninformation predictors of said second subset and including the said oneof the motion information predictors of said second subset, whereinthere are no duplicates among the further set of motion informationpredictors, the method further comprising removing duplicates from amongthe reduced subset of motion information predictors and the further setof motion information predictors to provide a non-duplicate set ofmotion information predictors.

In an embodiment, processing of the second subset of the first set ofmotion information predictors further comprises: generating furthermotion information predictors based on the reduced subset of motioninformation predictors to provide a further second subset of motioninformation predictors; and removing duplicates from among the motioninformation predictors of the further second subset of motioninformation predictors and the non-duplicate set of motion informationpredictors to provide a second non-duplicate set of motion informationpredictors.

In an embodiment, the method includes adding, to the secondnon-duplicate set of motion information predictors, a motion informationpredictor resulting from the processing of the first subset of motioninformation predictors which is not a duplicate of any of the motioninformation predictors of the second non-duplicate set of motioninformation predictors to obtain the final set of motion informationpredictors.

According to a second aspect of the invention there is provided a devicefor deriving at least one motion information predictor for encoding ordecoding of an image portion of an image by motion compensation withrespect to at least one reference image portion, the device comprising:means for obtaining, at least two distinct first and second subsets ofmotion information predictors of a first set of motion informationpredictors; first processing means for processing the first subset ofmotion information predictors; and second processing means forprocessing the second subset of motion information predictors, whereinthe second processing means is operable to perform at least part of theprocessing of the second subset of motion information predictorsconcurrently with at least part of the processing of the first subset ofmotion information predictors performed by the first processing means;and means for obtaining, based on motion information predictorsresulting from the processing of the first subset of motion informationpredictors and the processing of the second subset of motion informationpredictors, a final set of motion information predictors usable forpredicting said image portion from the reference image portion.

In an embodiment, the first subset comprises at least one temporalmotion information predictor and the second subset comprises at leastone spatial motion information predictor.

In an embodiment, the first processing means is operable to temporallyscale the or each temporal motion information predictor based on atemporal difference between the image of the image portion to be encodedand the image of the reference image portion.

In an embodiment, the second processing means is operable to generate aset of non-duplicate motion information predictors in which there are noduplicates among the motion information predictors of the said set.

In an embodiment, the second processing means is operable to generateone or more additional motion information predictors based on the motioninformation predictors of the second subset.

In an embodiment, the second processing means is operable to combine oneor more motion information predictors of the second subset, and/or addan offset to one or more information predictors of the second subset.

In an embodiment, the second processing means is operable to: removeduplicates from among the motion information predictors of said secondsubset, in the case where the second subset contains one or more motioninformation predictors which are the same, to provide a reduced subsetof motion information predictors; and generate further motioninformation predictors based on the reduced subset of motion informationpredictors to provide a further second subset of motion informationpredictors.

In a related aspect, there may independently be provided a device forderiving at least one motion information predictor for encoding ordecoding of an image portion of an image by motion compensation withrespect to at least one reference image portion, the device comprising:means for obtaining, at least two distinct first and second subsets ofmotion information predictors of a first set of motion informationpredictors (801-807), the first subset comprising at least one temporalmotion information predictor and the second subset comprising at leastone spatial motion information predictor and excluding any temporalmotion information predictor; first processing means (808, 809) forprocessing the first subset of motion information predictors; and secondprocessing means (808, 815, 817) for processing the second subset ofmotion information predictors; and means for obtaining (819), based onmotion information predictors (818, 814) resulting from the processingof the first subset of motion information predictors and the processingof the second subset of motion information predictors, a final set (820)of motion information predictors usable for predicting said imageportion from the reference image portion; wherein the second processingis operable to remove duplicates from among the motion informationpredictors of said second subset only, in the case where the secondsubset contains one or more motion information predictors which are thesame, to provide a reduced subset of motion information predictors(816).

In an embodiment, the first processing means is operable to performscaling of the temporal motion information predictor of the first subsetconcurrently with the operations of removing duplicates and generatingfurther motion information predictors of the second subset performed bythe second processing means.

In an embodiment, the device includes suppression means for removingduplicates from among the motion information predictors resulting fromthe processing of the first subset of motion information predictors andthe processing of the second subset of motion information predictors, inthe case where one or more motion information predictors resulting fromthe processing of the first subset of motion information predictors andthe processing of the second subset of motion information predictors arethe same, to provide the final set of motion information predictorsusable for encoding said image portion such that are no duplicates amongthe final set of motion information predictors.

In an embodiment, the second processing means is operable to removeduplicates from among the motion information predictors of the furthersecond subset of motion information predictors in the case where thefurther second subset contains one or more motion information predictorswhich are the same, to provide a second reduced subset of motioninformation predictors.

In an embodiment, the second processing means is operable to removeduplicates from among the motion information predictors of the furthersecond subset concurrently with scaling of the temporal motioninformation predictor of the first subset performed by the firstprocessing means.

In an embodiment, the device includes means operable to add, to thesecond reduced subset of motion information predictors, a motioninformation predictor, resulting from the processing of the first subsetof motion information predictors, which is not a duplicate of any of themotion information predictors of the second reduced subset of motioninformation predictors to obtain the final set of motion informationpredictors.

In an embodiment, the device includes means for adding, to the reducedsubset of motion information predictors, a motion information predictorresulting from the processing of the first subset of motion informationpredictors which is not a duplicate of any of the motion informationpredictors of the reduced subset of motion information predictors; andwherein the final set of motion information predictors comprises nonduplicate motion vectors from among the motion vector predictors of thereduced subset of motion information predictors and the further secondsubset of motion information predictors.

In an embodiment, the device includes means for estimating the durationof the processing of the first subset wherein the processing of thesecond subset performed by the second processing means concurrently withthe processing of the first subset performed by the first processingmeans is based on the estimation of the duration of the processing ofthe first subset.

In an embodiment, the device includes means for estimating the durationof the processing of the first subset wherein the motion informationpredictors resulting from the processing of the second subset which areadded to the motion information predictors resulting from the processingof the first subset to obtain the final set of motion informationpredictors is based on the duration of the processing of the firstsubset.

In an embodiment, the device includes means for determining, based onthe temporal difference between the image of the image portion and theimage of the reference image portion, whether or not a temporal scalingprocess is to be applied to the first subset of motion informationpredictors; and wherein in the case where it is determined that atemporal scaling process is to be applied, the first processing means isoperable to perform temporal scaling the motion information predictorsof the first subset of motion information predictors based on thetemporal difference between the image of the image portion and the imageof the reference image portion; otherwise, in the case where it isdetermined that a temporal scaling process is not to be applied, thefirst processing means is operable to remove duplicates from among themotion information predictors of the first subset of motion informationpredictors such that a reduced subset comprising non-duplicate motioninformation predictors from among the motion information predictors ofthe first subset of motion information predictors and the second subsetof motion information predictors is provided by processing performed bythe first processing means and the second processing means.

In an embodiment, the device includes suppression means for obtainingthe final set of motion information predictors wherein in the case whereit is determined that a temporal scaling process is to be applied, thesuppression means is operable to obtain the final set of predictors byremoving duplicates from among the motion information predictorsresulting from the concurrent processing of the first subset of motioninformation predictors and the second subset of motion informationpredictors; otherwise in the case where it is determined that a temporalscaling process is not to be applied, the first or second processingmeans is operable to obtain further motion information predictors, basedon the reduced subset to provide a further second subset of motioninformation predictors and the suppression means is operable to removeduplicates from among the further second subset of motion informationpredictors.

In an embodiment, the device includes means for determining thecomplexity of the temporally scaling process of the first subset ofmotion information predictors and suppression means for obtaining thefinal set of motion information predictors which are non-duplicate;wherein, in the case where it is determined that the temporal scalingprocess will last for a longer duration than a predetermined durationthreshold, the suppression means is operable to remove duplicates fromamong the motion information predictors resulting from the processing ofthe first subset of motion information predictors and the processing ofthe second subset of motion information predictors;

otherwise, in the case where it is determined that the temporal scalingprocess will last for a shorter duration than a predetermined durationthreshold, the suppression means is operable to add to the reducedsubset of motion information predictors obtained from the second subsetof motion vector predictors, a motion information predictor resultingfrom processing of the first subset of motion information predictorswhich is not a duplicate of any of the motion information predictors ofthe reduced subset of motion information predictors; wherein the finalset of motion information predictors comprises non duplicate motioninformation predictors from among the motion information predictors ofthe reduced subset of motion information predictors and the furthersecond subset of motion information predictors.

In an embodiment, the second processing means comprises means forremoving duplicates from among the motion information predictors of saidsecond subset to provide a reduced subset of motion informationpredictors; and means for generating a further set of motion informationpredictors based on one of the motion information predictors of saidsecond subset and including the said one of the motion informationpredictors of said second subset, wherein there are no duplicates amongthe further set of motion information predictors, the device furthercomprising suppression means for removing duplicates from among thereduced subset of motion information predictors and the further set ofmotion information predictors to provide a non-duplicate set of motioninformation predictors.

In an embodiment, the second processing means further comprises meansfor generating further motion information predictors based on thereduced subset of motion information predictors to provide a furthersecond subset of motion information predictors; and means for removingduplicates from among the motion information predictors of the furthersecond subset of motion information predictors and the non-duplicate setof motion information predictors to provide a second non-duplicate setof motion information predictors.

In an embodiment, the suppression means are operable to add, to thesecond non-duplicate set of motion information predictors, a motioninformation predictor resulting from the processing of the first subsetof motion information predictors which is not a duplicate of any of themotion information predictors of the second non-duplicate set of motioninformation predictors to obtain the final set of motion informationpredictors.

According to a third aspect of the invention there is provided a methodof deriving at least one motion information predictor for encoding ordecoding of an image portion of an image by motion compensation withrespect to at least one reference image portion, wherein for said imageportion to be encoded or decoded, the method comprises: providing, forprocessing, at least two distinct first and second subsets of motioninformation predictors of a first set of motion information predictors;estimating a duration for processing at least one of the first andsecond subsets of motion information predictors based on datarepresentative of the at least one subset; in dependence upon theestimated processing duration, processing of the motion informationpredictors of the first set comprising either: processing the firstsubset of motion information predictors and processing the second subsetof motion information predictors wherein at least part of the processingof the second subset of motion information predictors is performedconcurrently with at least part of the processing of the first subset ofmotion information predictors, or processing the first and secondsubsets of motion information predictors together; and obtaining, basedon motion information predictors resulting from the processing of themotion information predictors of the first set, a final set of motioninformation predictors usable for predicting said image portion from thereference image portion.

In an embodiment the method includes comparing a duration of time forprocessing the first subset of motion information predictors based witha duration of time for processing the second subset of motioninformation predictors wherein the processing of the first set of motioninformation predictors is based on the comparison.

In an embodiment the method includes comparing the duration of time forprocessing the first subset and/or the duration of time for processingthe second subset with a predetermined threshold wherein the processingof the first set of motion information predictors is based on thecomparison.

In an embodiment the method includes processing of the first subsetcomprises a temporal scaling process of one or motion informationpredictors of the first subset.

In an embodiment the method includes the data representative of thefirst subset and/or the second subset comprises the data of each motioninformation predictor of the first subset and/or the second subset

In an embodiment the method includes the data of each motion informationpredictor comprises the temporal distance for a temporal scalingprocess.

In an embodiment the method includes the data representative of thefirst subset and/or the second subset comprises the number of motioninformation predictors of the or each subset In an embodiment the methodincludes data representative of the first subset and/or the secondsubset comprises the maximum number of operations for processing thefirst subset and/or the second subset.

According to a fourth aspect of the invention there is provided a devicedevice for deriving at least one motion information predictor forencoding or decoding of an image portion of an image by motioncompensation with respect to at least one reference image portion,wherein the device comprises:

means for obtaining, at least two distinct first and second subsets ofmotion information predictors of a first set of motion informationpredictors;

means for estimating a duration for processing at least one of the firstand second subsets of motion information predictors based on datarepresentative of the at least one subset;

first processing means for processing the first subset of motioninformation predictors and second processing means for processing thesecond subset of motion information predictors in dependence upon theestimated processing duration, the second processing means beingoperable to either:

perform at least part of the processing of the second subset of motioninformation predictors concurrently with at least part of the processingof the first subset of motion information performed by the firstprocessing means predictors, or

process the first and second subsets of motion information predictorstogether; and

the device further comprising means for obtaining, based on motioninformation predictors resulting from the processing of the motioninformation predictors of the first set, a final set of motioninformation predictors usable for predicting said image portion from thereference image portion.

In an embodiment the device is provided with comparison means forcomparing a duration of time for processing the first subset of motioninformation predictors based with a duration of time for processing thesecond subset of motion information predictors wherein the processing ofthe first set of motion information predictors performed by the firstprocessing means is based on the comparison.

In an embodiment the device is provided with comparison means forcomparing the duration of time for processing the first subset and/orthe duration of time for processing the second subset with apredetermined threshold wherein the processing of the first set ofmotion information predictors performed by the first processing means isbased on the comparison.

In an embodiment the first processing means is operable to perform atemporal scaling process of one or motion information predictors of thefirst subset.

In an embodiment the data representative of the first subset and/or thesecond subset comprises the data of each motion information predictor ofthe first subset and/or the second subset

In an embodiment the data of each motion information predictor comprisesthe temporal distance for a temporal scaling process.

In an embodiment the data representative of the first subset and/or thesecond subset comprises the number of motion information predictors ofthe or each subset

In an embodiment the data representative of the first subset and/or thesecond subset comprises the maximum number of operations for processingthe first subset and/or the second subset

A further aspect of the invention provides a method of deriving at leastone motion information predictor for encoding or decoding of an imageportion of an image by motion compensation with respect to at least onereference image portion, wherein for said image portion to be encoded ordecoded, the method comprises processing the motion informationpredictors of a first set of motion information predictors to obtain afinal set of motion information predictors usable for predicting saidimage portion from the reference image portion; wherein the processingof the first set of motion information predictors comprises:sub-dividing the first set into at least two distinct first and secondsubsets of motion information predictors; estimating a duration forprocessing at least one of the first and second subsets of motioninformation predictors based on data representative of the at least onesubset; in dependence upon the estimated processing duration, either:performing the processing of the first set of motion informationpredictors using the sub-division in such a way that at least part ofthe processing of the second subset of motion information is performedconcurrently with at least part of the processing of the first subset ofmotion information predictors, or performing the processing of the firstset of motion information predictors without using the sub-division.

A yet further aspect of the invention provides a device for deriving atleast one motion information predictor for encoding or decoding of animage portion of an image by motion compensation with respect to atleast one reference image portion, wherein the device comprisesprocessing means for processing the motion information predictors of afirst set of motion information predictors to obtain a final set ofmotion information predictors usable for predicting said image portionfrom the reference image portion; wherein the processing means comprisesmeans for sub-dividing the first set into at least two distinct firstand second subsets of motion information predictors; means forestimating a duration for processing at least one of the first andsecond subsets of motion information predictors based on datarepresentative of the at least one subset; the processing means beingoperable to, in dependence upon the estimated processing duration,either: perform the processing of the first set of motion informationpredictors using the sub-division in such a way that at least part ofthe processing of the second subset of motion information is performedconcurrently with at least part of the processing of the first subset ofmotion information predictors, or perform the processing of the firstset of motion information predictors without using the sub-division.

An even further aspect of the invention provides a method of deriving atleast one motion information predictor for encoding or decoding of animage portion of an image by motion compensation with respect to atleast one reference image portion, wherein for said image portion to beencoded, the method comprises obtaining a first set of motioninformation predictors and concurrent processing of at least twodistinct subsets of motion information predictors of the first set ofmotion information predictors, the concurrent processing providing afinal set of motion information predictors usable for predicting saidimage portion from the reference image portion.

A fifth aspect of the invention provides a method of encoding a sequenceof digital images into a bitstream, at least one portion of an imagebeing encoded by motion compensation with respect to a reference imageportion, wherein, for at least one image portion to encode, the methodcomprises: obtaining at set of motion information predictors usable formotion prediction of the image portion with respect to the at least onereference image portion in accordance with the method of any of theembodiments of the first or third aspect of the invention; selecting atleast one motion information predictor from the set of informationpredictors for encoding the image portion; and encoding the imageportion using the selected at least one motion information predictor.

The method may include encoding an information item identifying theselected motion information predictor.

A sixth aspect of the invention provides an encoding device for encodinga sequence of images into a bitstream, at least one portion of an imagebeing encoded by motion compensation with respect to a reference imageportion, the encoding device comprising: a device for deriving at leastone motion information predictor in accordance with any of theembodiments of the second or the fourth aspect of the invention;selection means selecting at least one motion information predictor fromthe set of information predictors for encoding the image portion; andencoding means for encoding the image portion using the selected atleast one motion information predictor.

A seventh aspect of the invention provides a method of decoding abitstream comprising an encoded sequence of images, at least one portionof an image having been encoded by motion compensation with respect to areference image portion, the method comprising for at least one imageportion to be decoded: obtaining at set of motion information predictorsusable for motion prediction of the image portion with respect to the atleast one reference image portion in accordance with the method of anyone of the embodiments of the first or third aspect of the invention;selecting at least one motion information predictor from the set ofinformation predictors for decoding the image portion; and decoding theimage portion using the selected at least one motion informationpredictor.

An eighth aspect of the invention provides a decoding device fordecoding a bitstream comprising an encoded sequence of images, at leastone portion of an image having been encoded by motion compensation withrespect to a reference image portion, the decoding device comprising:

a device for deriving at least one motion information predictor inaccordance with the device of any one of the embodiments of the secondor fourth aspects of the invention; selection means for selecting atleast one motion information predictor from the set of informationpredictors for decoding the image portion; and decoding means fordecoding the image portion using the selected at least one motioninformation predictor.

It will be appreciated that embodiments of the different aspects of theinvention may be used for P and B slices and for both uni andbi-directional Inter predictions.

At least parts of the methods according to the invention may be computerimplemented. Accordingly, the present invention may take the form of anentirely hardware embodiment, an entirely software embodiment (includingfirmware, resident software, micro-code, etc.) or an embodimentcombining software and hardware aspects that may all generally bereferred to herein as a “circuit”, “module” or “system”. Furthermore,the present invention may take the form of a computer program productembodied in any tangible medium of expression having computer usableprogram code embodied in the medium.

Since the present invention can be implemented in software, the presentinvention can be embodied as computer readable code for provision to aprogrammable apparatus on any suitable carrier medium. A tangiblecarrier medium may comprise a storage medium such as a floppy disk, aCD-ROM, a hard disk drive, a magnetic tape device or a solid statememory device and the like. A transient carrier medium may include asignal such as an electrical signal, an electronic signal, an opticalsignal, an acoustic signal, a magnetic signal or an electromagneticsignal, e.g. a microwave or RF signal. Embodiments of the invention willnow be described, by way of example only, and with reference to thefollowing drawings in which:—

FIG. 1 is a schematic diagram of a set of motion vector predictors usedin a motion vector prediction process in the context of embodiments ofthe present invention;

FIG. 2 is a flow chart illustrating steps of a process of the prior artfor deriving a set of motion vector predictors;

FIG. 3 is a block diagram illustrating components of a processing devicein which embodiments of the invention may be implemented;

FIG. 4 is a block diagram illustrating components of an encoder deviceaccording to embodiments of the invention;

FIG. 5 is a block diagram illustrating components of a decoder deviceaccording to embodiments of the invention;

FIG. 6 is a flow chart illustrating steps of a method for obtaining aset of motion information predictors according to a first embodiment ofthe invention;

FIG. 7 is a flow chart illustrating steps of a method for obtaining aset of motion information predictors according to a second embodiment ofthe invention;

FIG. 8 is a flow chart illustrating steps of a method for obtaining aset of motion information predictors according to a third embodiment ofthe invention;

FIG. 9 is a flow chart illustrating steps of a method for obtaining aset of motion information predictors according to a fourth embodiment ofthe invention;

FIGS. 10(a)-10(c) schematically illustrate schemes for the generation ofmotion vector predictors in accordance with one or more embodiments ofthe invention; and

FIG. 11 is a schematic diagram for illustrating a process of scaling ofa temporal predictor used in embodiments of the invention.

FIG. 3 schematically illustrates a processing device 200 configured toimplement at least one embodiment of the present invention. Theprocessing device 200 may be a device such as a micro-computer, aworkstation or a light portable device. The device 200 comprises acommunication bus 213 to which there are preferably connected:

-   -   a central processing unit 211, such as a microprocessor, denoted        CPU;    -   a read only memory 207, denoted ROM, for storing computer        programs for implementing the invention;    -   a random access memory 212, denoted RAM, for storing the        executable code of the method of embodiments of the invention as        well as the registers adapted to record variables and parameters        necessary for implementing the method of encoding a sequence of        digital images and/or the method of decoding a bitstream        according to embodiments of the invention; and    -   a communication interface 202 connected to a communication        network 203 over which digital data to be processed are        transmitted.

Optionally, the apparatus 200 may also include the following components:

-   -   a data storage means 204 such as a hard disk, for storing        computer programs for implementing methods of one or more        embodiments of the invention and data used or produced during        the implementation of one or more embodiments of the invention;    -   a disk drive 205 for a disk 206, the disk drive being adapted to        read data from the disk 206 or to write data onto said disk;    -   a screen 209 for displaying data and/or serving as a graphical        interface with the user, by means of a keyboard 210 or any other        pointing means.

The apparatus 200 can be connected to various peripherals, such as forexample a digital camera 200 or a microphone 208, each being connectedto an input/output card (not shown) so as to supply multimedia data tothe apparatus 200.

The communication bus provides communication and interoperabilitybetween the various elements included in the apparatus 200 or connectedto it. The representation of the bus is not limiting and in particularthe central processing unit is operable to communicate instructions toany element of the apparatus 200 directly or by means of another elementof the apparatus 200.

The disk 206 can be replaced by any information medium such as forexample a compact disk (CD-ROM), rewritable or not, a ZIP disk or amemory card and, in general terms, by an information storage means thatcan be read by a microcomputer or by a microprocessor, integrated or notinto the apparatus, possibly removable and adapted to store one or moreprograms whose execution enables the method of encoding a sequence ofdigital images and/or the method of decoding a bitstream according tothe invention to be implemented.

The executable code may be stored either in read only memory 207, on thehard disk 204 or on a removable digital medium such as for example adisk 206 as described previously. According to a variant, the executablecode of the programs can be received by means of the communicationnetwork 203, via the interface 202, in order to be stored in one of thestorage means of the apparatus 200 before being executed, such as thehard disk 204.

The central processing unit 211 is adapted to control and direct theexecution of the instructions or portions of software code of theprogram or programs according to the invention, instructions that arestored in one of the aforementioned storage means. On powering up, theprogram or programs that are stored in a non-volatile memory, forexample on the hard disk 204 or in the read only memory 207, aretransferred into the random access memory 212, which then contains theexecutable code of the program or programs, as well as registers forstoring the variables and parameters necessary for implementing theinvention.

In this embodiment, the apparatus is a programmable apparatus which usessoftware to implement the invention. However, alternatively, the presentinvention may be implemented in hardware (for example, in the form of anApplication Specific Integrated Circuit or ASIC).

FIG. 4 illustrates a block diagram of an encoder according to at leastone embodiment of the invention. The encoder is represented by connectedmodules, each module being adapted to implement, for example in the formof programming instructions to be executed by the CPU 211 of device 200,at least one corresponding step of a method implementing at least oneembodiment of encoding an image of a sequence of images according to oneor more embodiments of the invention.

An original sequence of digital images i0 to in 301 is received as aninput by the encoder 30. Each digital image is represented by a set ofsamples, known as pixels.

A bitstream 310 is output by the encoder 30 after implementation of theencoding process.

The bitstream 310 comprises a plurality of encoding units or slices,each slice comprising a slice header for transmitting encoding values ofencoding parameters used to encode the slice and a slice body,comprising encoded video data.

The input digital images i0 to in 301 are divided into blocks of pixelsby module 302. The blocks correspond to image portions and may be ofvariable sizes (e.g. 4×4, 8×8, 16×16, 32×32 pixels). A coding mode isselected for each input block. Two families of coding modes areprovided: coding modes based on spatial prediction coding (Intraprediction), and coding modes based on temporal prediction (Intercoding, Bidir, SKIP). The possible coding modes are tested.

Module 303 implements Intra prediction, in which the given block to beencoded is predicted by a predictor computed from pixels of theneighbourhood of said block to be encoded. An indication of the selectedIntra predictor and the difference between the given block and itspredictor is encoded to provide a residual if the Intra coding isselected.

Temporal prediction is implemented by motion estimation module 304 andmotion compensation module 305. Firstly a reference image from among aset of reference images 316 is selected, and a portion of the referenceimage, also called reference area or image portion, which is the closestarea to the given block to be encoded, is selected by the motionestimation module 304. Motion compensation module 305 then predicts theblock to be encoded using the selected area. The difference between theselected reference area and the given block, also called a residualblock, is computed by the motion compensation module 305. The selectedreference area is indicated by a motion vector.

Thus in both cases (spatial and temporal prediction), a residual iscomputed by subtracting the prediction from the original predictedblock.

In the INTRA prediction implemented by module 303, a predictiondirection is encoded. In the temporal prediction, at least one motionvector is encoded.

Information relative to the motion vector and the residual block isencoded if the Inter prediction is selected. To further reduce thebitrate, the motion vector is encoded by difference with respect to amotion vector predictor. Motion vector predictors of a set of motioninformation predictors is obtained from the motion vectors field 318 bya motion vector prediction and coding module 317.

The set of motion vector predictors from which a motion vector predictoris selected for encoding of a current motion vector is generated as willbe explained in more detail hereafter with respect to any one of FIGS. 7to 10. For a given current block to be encoded, in some embodiments ofthe invention a number N of motion vector predictors is determined, andconsequently the index of the selected motion vector predictor, which isan item of information representative of the selected motion vectorpredictor, can be encoded using a predetermined number of bits accordingto the number N of motion vector predictors. This predetermined numberof bits can be also retrieved by the decoder even in case of losses,therefore it may be ensured that the decoder will be able to parse thebitstream even in case of errors or losses. The N motion vectorpredictors are selected according to various embodiments of theinvention to be all different from one another so as to enhance thecompression efficiency.

The encoder 30 further comprises a selection module 306 for selection ofthe coding mode. The selection module 306 applies an encoding costcriterion, such as a rate-distortion criterion, to determine which isthe best mode between the spatial prediction mode and the temporalprediction mode. In order to further reduce redundancies a transform isapplied by transform module 307 to the residual block, the transformeddata obtained is then quantized by quantization module 308 and entropyencoded by entropy encoding module 309. Finally, the encoded residualblock of the current block being encoded is inserted into the bitstream310, along with the information relative to the predictor used such asthe index of the selected motion vector predictor. For the blocksencoded in ‘SKIP’ mode, only a reference to the predictor is encoded inthe bitstream, without any residual block.

The encoder 30 also performs decoding of the encoded image in order toproduce a reference image for the motion estimation of the subsequentimages. This enables the encoder and the decoder receiving the bitstreamto have the same reference frames. The inverse quantization module 311performs inverse quantization of the quantized data, followed by aninverse transform by reverse transform module 312. The reverse intraprediction module 313 uses the prediction information to determine whichpredictor to use for a given block and the reverse motion compensationmodule 314 actually adds the residual obtained by module 312 to thereference area obtained from the set of reference images 316.Optionally, a deblocking filter 315 is applied to remove the blockingeffects and enhance the visual quality of the decoded image. The samedeblocking filter is applied at the decoder, so that, if there is notransmission loss, the encoder and the decoder apply the sameprocessing.

FIG. 5 illustrates a block diagram of a decoder 40 according to at leastone embodiment of the invention. The decoder is represented by connectedmodules, each module being adapted to implement, for example in the formof programming instructions to be executed by the CPU 211 of device 200,a corresponding step of a method implementing an embodiment of theinvention.

The decoder 40 receives a bitstream 401 comprising encoding units, eachone being composed of a header containing information on encodingparameters and a body containing the encoded video data. As explainedwith respect to FIG. 4, the encoded video data is entropy encoded, andthe motion vector predictors' indexes are encoded, for a given block, ona predetermined number of bits. The received encoded video data isentropy decoded by module 402. The residual data are then dequantized bymodule 403 and then a reverse transform is applied by module 404 toobtain pixel values.

The mode data are also entropy decoded and based on the mode, an INTRAtype decoding or an INTER type decoding is performed.

In the case of INTRA mode, an INTRA predictor is determined by intrareverse prediction module 405 based on the intra prediction modespecified in the bitstream.

If the mode is INTER, the motion prediction information is extractedfrom the bitstream so as to find the reference area used by the encoder.The motion prediction information is composed of the reference frameindex and the motion vector residual. The motion vector predictor isadded to the motion vector residual in order to obtain the motion vectorby motion vector decoding module 410.

Motion vector decoding module 410 applies motion vector decoding foreach current block encoded by motion prediction. Once an index of themotion vector predictor for the current block has been obtained theactual value of the motion vector associated with the current block canbe decoded and used to apply reverse motion compensation by module 406.The reference area indicated by the decoded motion vector is extractedfrom a reference image 408 to apply the reverse motion compensation 406.The motion vector field data 411 is updated with the decoded motionvector in order to be used for the inverse prediction of the nextdecoded motion vectors.

Finally, a decoded block is obtained. A deblocking filter 407 isapplied; similarly to the deblocking filter 315 applied at the encoder.A decoded video signal 409 is finally provided by the decoder 40.

FIG. 6 is a flow chart illustrating steps of a method according to afirst embodiment of the invention for deriving a set of potential motioninformation predictors suitable for the encoding of an image portion ofan image with respect to a reference image portion. In the first step ofthe method, 7 block positions are considered (701 to 707). Thesepositions correspond to the spatial and temporal positions depicted inFIG. 1. Module 708 verifies the availability of the motion vectors ofthe 7 block positions and selects 4 motion vectors as motion vectorpredictors. In this module, a motion vector is available as a predictorif it exists and if motion vector block is not Intra coded. Theselection and the verification of the 4 motion vector predictors aredescribed under the following conditions:

-   -   If the “Left” motion vector (701) is available (if it exists and        if this block is not Intra coded), the motion vector of the        “Left” block is selected and used as the predictor 1 (610).    -   If the “Above” motion vector (702) is available, the motion        vector of the “Above” block is selected and used as the        predictor 2 (711).    -   If the “Above Right” motion vector (703) is available, the        motion vector of the “Above Right” block is selected and used as        the predictor 3 (712).    -   If the “Below Left” motion vector (704) is available, the motion        vector of the “Below Left” block is selected and used as the        predictor 4 (713).    -   If one (or more) of these predictors is not available and if the        “Above Left” motion vector (705) is available, the motion vector        of the “Above Left” block is added to the set of selected motion        vector predictors after the added spatial predictor.    -   If the “H” motion vector is available, the motion vector of the        “H” block is selected and used as the predictor 5 (714). If the        “H” block is not available, the availability of the “collocated”        motion vector (the motion vector of the block at the same        position in the current block) is checked and, if the collocated        motion vector is available, it is used as the temporal        predictor. The availability check of the module 708 requires 1        cycle.

Since the set of motion vector predictors selected at the beginning ofthe process contains only the spatial predictors 1, 2, 3, 4 thecomplexity of the selection process 715 is reduced compared to theselection process of the prior art in FIG. 2 comprising 4 spatial and 1temporal predictors.

The suppression process consists in comparing each selected predictor toall the other selected predictors and in removing those selectedpredictors which are equal to another selected predictor (whileretaining the other selected predictor of which the removed predictor isa duplicate) to provide a set of predictors in which none of thepredictors are duplicates of one another. The suppression process for Pslices takes into account the values of the motion vectors and theirreference frame indexes. Accordingly, the two components of a motionvector and its reference frame index are compared to all thecorresponding components of the other motion vectors and only if thesethree values are equal, is the predictor is removed from (or not addedto) the set. For a B frame, this criterion can be extended to thedirection and the lists. Thus, a predictor is considered as a duplicatepredictor if it uses the same direction, the same lists (L0, L1, or L0and L1), the same reference frame indexes and the same value of themotion vectors (MV_L0 and MV_L1 for bi prediction) in the set ofselected motion vectors. The suppression process lasts 1 cycle when 5predictors at most need to be compared. Indeed, it may be consideredthat 12 comparisons can be computed in 1 cycle. The maximum number ofcomparisons for the suppression process in the most complex case isequal to the Sum of 0 to N−1. Since the maximum number of predictors atthe beginning of the suppression process is 4 instead of 5, the maximumnumber of comparisons to be performed is 6(i.e. 3+2+1=6) compared to 10as for the 5 selected predictors of the prior art of FIG. 2. At the endof this suppression process 715, a reduced set of predictors 716 isgenerated. The reduced motion vector predictor set 716 contains at most4 predictors compared to 5 in the prior art.

Motion vector predictor's generation module 717 generates new predictorcandidates based on the predictors of the reduced motion vectorpredictor set. Several schemes for creating such predictors may be usedand one such scheme will be described later with reference to FIG. 10(a)to (c). It may be considered that the process performed by motion vectorpredictor's generation module lasts at least 1 cycle and produces asecond set of predictors 718. Since the set of reduced predictors 716generally contains less predictors than the reduced predictors set 616of the prior art illustrated in FIG. 2, on average less combinedpredictors and scaled predictors are generated in the reduced motionvector predictor set 717 compared to that of the prior art and thecomplexity of the process is reduced.

Next, suppression processing module 721 which operates in a similarmanner to the suppression process module 715, removes the duplicatecandidates from the second predictors set 718 and the reduced predictorsset 716 by comparing the respective motion vector components andassociated motion information parameters. In the prior art illustratedin FIG. 2, the duration of this particular process can reach 3 cyclesdepending on the number of predictors generated in the second predictorset 718, particularly in the case where the motion vector predictorgeneration of the current HEVC design is applied. Suppression process721 produces a second reduced set of motion vector predictors 722.

Finally, the temporal predictor 714 is compared to the second reducedset of motion vector predictors 722 in the module 719. In thesuppression and reordering processing performed by module 719, thetemporal predictor is compared to, at most, 5 predictors in order todetermine if the temporal predictor is a duplicate predictor. If it is anon-duplicate predictor, the temporal predictor is inserted into thelist of predictors just before the last non duplicate spatial predictor.The temporal position has been determined by the suppression processingmodule 715 and transmitted to the processing module 719, and correspondsto the number of predictors in 715. The list of predictors is truncatedif it contains more than 5 predictors in order to produce the final setof predictors 720. It may be noted that the maximum number ofcomparisons performed by the module 719 is 5 in the most complex casewhich is a reduction compared to that of the suppression module 619 ofthe prior art illustrated in FIG. 2.

In an alternative embodiment the suppression processing module 719 mayoperate in the same manner to the suppression processing module 619 ofthe prior art. In such a case the temporal predictor is only added tothe set of predictors if the reduced set of predictors 722 contains atmost 4 predictors. Otherwise it is added to the end of the list ofpredictors.

FIG. 7 illustrates a second embodiment of the invention. The maindifference with respect to the embodiment of FIG. 6 is that the Motionvector predictor generation process performed by module 817 lasts for aduration of 2 cycles instead of 1 cycle as in the case of module 717 ofFIG. 6. In the case of FIG. 7, the suppression process for removingduplicate predictors of the second predictors set 818 is not executed inparallel to the temporal scaling process 809. Consequently, in FIG. 7,in the suppression module 819, the temporal predictor 814 is compared toboth the predictors of the reduced set of motion vector predictors 816and the predictors of the second predictors set 818. In this process iftemporal predictor 814 is a non-duplicate predictor of the motion vectorpredictors of reduced motion vector predictors set 816, the temporalpredictor 814 is added to the reduced set of motion vector predictorsafter the spatial predictors. Next, the predictors of the secondpredictor set 818 are compared to the predictors of the reduced set ofmotion vector predictors 816, with the temporal predictor 814 if added,and to the other predictors of the second predictors set 818.

The advantage of the processing of the embodiments of FIG. 6 or FIG. 7results from the full execution of the scaling process 709 in parallelwith the first suppression process 715 or 815 and the motion vectorpredictor generation process 717 or 817. According to the complexity ofeach process, additional suppression processes 721 can be included inthe method to predetermine a non-duplicate set in order to reduce thecomplexity of the final suppression process 719. Thus, in the firstembodiment of the invention it may be considered that the overallsuppression process is split into two suppression processes implementedby modules 721 and 719.

The parallel scaling process has a beneficial impact on the codingefficiency. Indeed, since the temporal predictor 714 or 814 is not usedto generate the second set of predictors 718 or 818 this has an impacton the generation of the motion vector predictors.

Steps of a method of generating a set of motion vector predictors inaccordance with a third embodiment of the invention is illustrated inthe flow chart of FIG. 8. The method according to the third embodimentof the invention further reduces the impact on the coding efficiency.

Selection module 908 operates in a similar manner to correspondingselection modules 708 and 808 of the first and second embodiments of theinvention to select 4 motion vectors 910 to 913, based on theiravailability, from spatial and temporal block positions 901 to 907.

The main difference is the use of a scaling decision module 923. In thescaling decision module 923 the temporal distance of the temporal motionvector and the temporal distance of the temporal predictor (predictornumber 5) are compared. For a uni-directional type of inter predictionthis means that the Picture Order Count (POC) difference between thetemporal frame (the frame of H and collocated blocks) and the referenceframe pointed to by the temporal motion vector (H or collocated) iscompared to the temporal distance between the current frame and thereference frame of the temporal predictor. If these temporal distancesare equal, the scaling decision module 923 returns the value “No”.Otherwise, it means that a scaling process is needed, and the scalingdecision module 923 returns the value “Yes”. For a Bi-directionalprediction type, the decision module 923 compares the temporal distancesfor each list and the returned decision depends on the decisions forboth lists. Thus, if for both lists no scaling is needed, scalingdecision module 923 returns the value “No” and if at least one scalingprocess is needed for one list, the scaling decision module 923 returnsthe value “Yes”.

If the scaling decision module 923 returns the value “No”, the temporalpredictor 5 (924) is used in the suppression process 915. Consequently,the generation of motion vector predictors 917 uses the value of thetemporal predictor 5 to generate the second set of predictors 918. Then,the suppression process 921 is applied to the reduced set of predictors916 and the set of second predictors 918. Next, a decision module 925makes a decision on the provision of the final set of motion vectorpredictors based on the decision of the scaling decision module 923—i.e.the decision made by scaling decision module 923 is used to determinewhether or not the reduced predictors set produced by the suppressionprocess 921 is the final predictor set—when a “No” is returned bydecision module 923 it is determined that the reduced predictors setproduced by the suppression process 921 is the final predictor set.Thus, when scaling decision module 923 returns a “No” indicating scalingis not required, the derivation of the predictors set operates in asimilar manner to the derivation of the set of predictors as illustratedin FIG. 2.

Otherwise, if the scaling decision module 923 returns the value “Yes”,indicating that the temporal predictor is scaled in module 909 toproduce a temporal predictor number 5 (914) it is determined that thereduced predictors set produced by the suppression process 921 is notthe final predictor set. In this case the suppression process module 915has not used the temporal predictor for the suppression process and themotion vector predictor generation module 917 has not used the temporalpredictor to create new predictors. Consequently, in a similar manner tothe process illustrated in the flow chart of FIG. 6, the scaling process909 of the temporal predictor 5 is executed in parallel to thegeneration of motion vector predictors 917. The scaling decision module925, after the second suppression process, returns the value “Yes”. Thusthe scaled temporal predictor 914 is compared to the predictors of thesecond reduced set of predictors 922 in the suppression process 919. Asin the case of the suppression process module 719 of FIG. 6, if thetemporal predictor 914 is a non-duplicate predictor of the predictors inthe second reduced set of predictors, the suppression and reorderingmodule 919 inserts the temporal predictor into the set of predictorsafter the first reduced predictors set 916 to provide the final set ofpredictors 920.

To summarize this embodiment, the scaling process 909 is executed inparallel to the generation process 917 of the second set 918 only if thetemporal predictor needs to be scaled.

If we consider that the generation of the motion vector predictors 917lasts 1 cycle, and if the temporal predictor does not need a scalingprocess, 4 cycles are needed to produce the Merge predictors set,otherwise 5 cycles are needed. Consequently the process is reduced by 2cycles in the most complex case as in the first embodiment. The mainadvantages of this embodiment compared to the previous one are the useof the temporal predictor for the generation of the second set of thepredictors only when the temporal predictor does not need scaling.Consequently, the coding efficiency may be improved compared to thefirst embodiment.

In an additional embodiment, it is possible to consider the complexityof the scaling process. For example, it may be possible to know if thescaling process requires only one cycle. One cycle is only needed if thesign of the motion vector predictor needs to be changed. In that case,the temporal predictor is available in the same time as the reducedpredictors set 916. Thus, the temporal predictor can be used for thesuppression process 921. In that case, the scaling decision module 925returns the value “Yes” and the module 922 and 919 are not needed toprovide the final set of predictors. Consequently, the duration of thederivation process is reduced by one cycle because the suppressionprocess 919 lasts 1 cycle.

FIG. 9 is flow chart illustrating a method of deriving a set of motionvector predictors in accordance with a fourth embodiment of theinvention. The flow chart of FIG. 9 is based on that of FIG. 6. As aconsequence the modules 1001 to 1020 and 1022 of FIG. 9 are respectivelythe same as the modules 701 to 720 and 720 of FIG. 6. The differencesare the use in parallel of the non-duplicate predictors by addingoffsets as will described in the generation of motion vector predictorswith respect to FIGS. 10(a)-(c). When the first predictor 11010 isdefined, module 1023 generates a list non-duplicate predictors. Asexplained with respect to FIG. 10(c), this process consists in addingoffsets to one or both motion vector components of the first predictor1010. The set of non-duplicate predictors 1024 contains 4 predictorswhich are all different to one another and different to the firstpredictor 1010 available after the availability check implemented by theselection processing module 1008. As a consequence, in this embodiment,the set of non-duplicate predictors 1024, when added to the firstpredictor 1010, contains 5 non-duplicate predictors as fixed for theMerge mode. The generation of non duplicate predictors is executed inparallel to the suppression process 1015. Suppression processing module1025 compares the non-duplicate predictors set 1024 with the reducedpredictors set 1016 in order to obtain only 5 predictors. Thenon-duplicate predictors set 1026 contains the reduced predictors set1016 followed by the non-duplicate predictors set generated in 1024. Itmay be noted that the suppression process 1025 generally requires amaximum of 6 comparisons. The most complex case happens when the reducedmotion vector predictors set 1016 contains 4 predictors. The set ofnon-duplicate predictors 1024 contains 4 predictors. Theoretically, thesuppression process requires 16 comparisons in the most complex case (4predictors of reduced motion vector predictors set 1016 by 4 predictorsof non-duplicate predictors set 1024). However, the motion vectorpredictors in the non-duplicate predictors set 1024 are different fromthe first predictor, so only the second, the third and the fourthpredictors of the reduced motion vector predictor set 1016 need to becompared to the set of non-duplicate motion vector predictors 1024. As aconsequence, 12 (4 by 3) comparisons are needed. The predictors are alldifferent to one another in the set of non-duplicate predictors 1024, soin the most complex case, if the 3 first predictors of the non-duplicatepredictors 1024 are equal to the 3 last predictors of reduced motionvector predictors set 1016, it can be assumed that the last predictor in1024 is different to the predictor of reduced motion vector predictorsset 1016. Thus, only 9 (3 by 3) comparisons are needed.

Next, a second set of motion vector predictors 1018 is generated bymotion vector predictor's generation module 1017. The suppression andreorder process 1021 checks if the motion vector predictors of thesecond predictors set 1018 are non-duplicate compared to thenon-duplicate set 1026 which already contains 5 predictors. If apredictor of the second predictors set 1018 is different from all theothers, it is inserted at the position of the number of predictors inthe reduced predictors set 1016 (after the predictors of the reducedmotion vector predictors set 1016 in the list). The subsequent steps1022, 1019, and 1020 operate in the same manner as the processing ofmodules 722, 719 and 720 of FIG. 6.

It may be noted that the generation of non-duplicate predictors 1023 canbe added at the end of the derivation process, after the suppressionprocess 1019. This would require an additional suppression process whichneeds one more cycle and would not result the same predictors setordering.

The fourth embodiment has several advantages. Firstly, in thisembodiment, each predictor position has a value. Consequently, themethod provides a more robust process than the current design of HEVC.Indeed, an encoder may use a predictor index without value at thedecoder which may cause decoder a crash. This can occur, for example,when network errors occur.

This embodiment compensates for the loss of coding efficiency of theparallel scaling. Moreover, this modification also compensates for theloss of coding efficiency of a reduction of the number of candidatesgenerated in the motion vectors predictors' generation of module 1017.With these non-duplicate predictors, only 2 predictors need to begenerated in 1021. Consequently, the suppression process 1021 needs only10 comparisons in the most complex case. Thus, only one cycle is neededinstead of 3 for the most complex case of the current HEVC designpresented in FIG. 2. With this simplification, only 5 cycles in the mostcomplex case are needed to derive the Merge predictors set instead of 11for the current HEVC design.

It will be appreciated that the fourth embodiment of FIG. 9 may beeasily combined with the third embodiment presented in FIG. 8.

Examples of processes for the generation of further motion vectors aspredictors implemented by the motion vector predictors generationmodules 717, 817, 917 and 1017 of FIGS. 6, 7, 8 and 9 respectively willnow be described with reference to FIGS. 10(a)-(c). The current HEVCdesign uses 3 schemes to add new predictors based on the current setgeneration. The first scheme is used for B slices. The motion vectorpredictor generation involves combining the predictors of the reducedpredictors set 716, 816, 916, 1016 of FIGS. 6, 7, 8 and 9 respectively.A combined predictor is generated by selecting the motion vector of listL0 of a first predictor and by selecting the motion vector of list L1from another predictor. For example, the first possible combinedpredictor has the motion vector (and ref index) from L0 of the firstpredictor of 716 and the motion vector (and ref index) from L1 of thesecond predictor of 716. In the current HEVC design, 12 possiblecombined predictors can be generated. FIG. 10(a) shows an example ofthis process.

The second scheme may only be used for B slices. The scaled predictorcomprises changing uni-directional predictors with bi-directionalpredictors. If a predictor of 716 is uni-directional, the motion vectoris created in the opposite list based on the initial motion vector. Forexample, if the first predictor of 716 is unidirectional and if itpoints to L0 with the ref index 0, the value of its motion vector isscaled to point to the ref index 0 of L1. The built predictor containsthe ref index 0 and the motion vector value for L0 and the ref index 0and the scaled vector for list L1. This new bidirectional predictor isadded to the second predictors set (718). This kind of predictorgeneration is very complex because it needs to scale motion vectors, sothis increases the number of cycles for the module 717 (3 cycles). Thusscaling process may be limited to inverse the sign of the motion vectorvalue component which can be executed in one cycle, instead of 3 for theclassical scaling process. FIG. 10(b) shows an example of thisgeneration.

Another method of generating new motion vector predictors is by changingbi-directional predictors to unidirectional predictors. In that case,when a predictor is bi-directional 2 new predictors can be generated(one for each list). This is a low complexity process compared to thescaled motion vector process of FIG. 10(a).

In the current design of HEVC, at the end of the list a “zero motionvector” value is added. For the Merge, the zero value is set for bothMotion vectors of L0 and L1. And if possible, the reference frame indexof each list is incremented to create other zero predictors. Thus, onlythe ref index is changed. If N ref index are used in both lists, N zerovectors can be added to the set of predictors. FIG. 10(c) illustrates anexample such a process of generation of motion vector predictors.

Moreover, it is possible to use non duplicate predictors by adding oneor more offsets to the components or several components of one availablepredictor of the initial set of predictors. For example, if only onepredictor is in the initial set of predictors, it is possible togenerate 4 predictors which are all different. For example, if weconsider that the predictor in the list is unidirectional, the firstpredictor is generated by adding an offset value on one component of thefirst motion vector. The second predictor is generated by adding theinverse offset to the first component. The third one is obtained byadding the offset to the second component and the fourth by adding theinverse offset to the second component. It may be noted that thisprocess can be applied on the first candidate, so that the predictor canbe derived before the suppression process 715.

FIG. 11 shows an example of a scaling for the temporal predictor asapplied in scaling modules 709, 809, 909 and 1009 of FIGS. 6, 7, 8, and9 respectively. In this figure, the collocated motion vector MVcol inreference frame Ref0 pointed to Ref2 with the POC (Picture Order Count)equal to N−3. The reference frame of the temporal predictor MVt has beendetermined and is equal to Ref0 (POC number equal to N−1). The temporaldistance iDiffPocD of the collocated motion vector is equal to the POCof Ref2 minus the POC of Ref0. Thus, its temporal distance is equal to:

iDiffPocD=(N−3)−(N−1)=2

In the same way, the temporal distance iDiffPocB which needs to becovered by the temporal predictor is equal to the POC of the currentframe N minus the POC of Ref0:

iDiffPocB=(N)−(N−1)=1

Theoretically, the scale motion vector for the temporal predictor isequal to:

MVt=(iDiffPocB*MVcol)/iDiffPocD

Thus in the example, each component (Horizontal and vertical) is dividedby 2. However in the current HEVC design, the scaling of a motion vectoris given by the following process:

-   -   The scaled factor is determined by the following formula:

iScale=(iDiffPocB*iX+32)>>6;

-   -   with iX

iX=(0x4000+abs(iDiffPocD/2))/iDiffPocD;

-   -   The MVt is then given by:

MVt=(iScale*MVcol+127+(iScale*MVcol<0))>>8

In these formulas:“>>” represents the shifting operator“abs” represents a function which returns the absolute value“0x4000” represents the value 16384

Embodiments of the invention thus provide a parallel derivation processwhich the aim of reducing the number of cycles needed to derive a set ofmotion vector predictors with a minor impact on the coding efficiency.

Although the present invention has been described hereinabove withreference to specific embodiments, the present invention is not limitedto the specific embodiments, and modifications will be apparent to askilled person in the art which lie within the scope of the presentinvention. Many further modifications and variations will suggestthemselves to those versed in the art upon making reference to theforegoing illustrative embodiments, which are given by way of exampleonly and which are not intended to limit the scope of the invention,that being determined solely by the appended claims. In particular thedifferent features from different embodiments may be interchanged, whereappropriate.

In the claims, the word “comprising” does not exclude other elements orsteps, and the indefinite article “a” or “an” does not exclude aplurality. The mere fact that different features are recited in mutuallydifferent dependent claims does not indicate that a combination of thesefeatures cannot be advantageously used.

1. A method of determining motion information predictor candidates for amotion information predictor for encoding an image portion in an imageto be encoded by inter prediction, the method comprising for the imageportion to be encoded: acquiring one or more spatial motion informationpredictor candidates from one or more image portions in the image to beencoded and one or more temporal motion information predictor candidatesfrom one or more image portions in an image different from the image tobe encoded; performing first processing on motion information predictorcandidates including the one or more spatial motion informationpredictor candidates but not including any temporal motion informationpredictor candidates for the image portion to be encoded, wherein thefirst processing comprises excluding a duplicate motion informationpredictor candidate; performing second processing on motion informationpredictor candidates including at least the one or more temporal motioninformation predictor candidates for the image portion to be encoded,wherein the second processing comprises excluding a duplicate motioninformation predictor candidate; obtaining, based on at least one ormore spatial motion information predictor candidates and one or moretemporal motion information predictor candidates resulting from thefirst and second processing, a set of motion information predictorcandidates for the motion information predictor.
 2. A method accordingto claim 1, wherein a motion information predictor candidate beingcapable of including a motion vector associated with a first indexcorresponding to a first reference picture list and a motion vectorassociated with a second index corresponding to a second referencepicture list, and wherein the method further comprises: generating oneor more additional motion information predictor candidates by combiningmotion vectors from first and second motion information predictorcandidates included in the set of motion information predictorcandidates, the motion vector from the first motion informationpredictor candidate being associated with the first index and the motionvector from the second motion information predictor candidate beingassociated with the second index; and including the generated one ormore additional motion information predictor candidates in the set ofmotion information predictor candidates.
 3. A method according to claim1, wherein, in a case where a motion information of an above imageportion of the image portion to be encoded is available, the one or morespatial motion information predictor candidates are able to include themotion information of the above image portion.
 4. A method ofdetermining motion information predictor candidates for a motioninformation predictor for decoding of an image portion in an image to bedecoded by inter prediction, the method comprising for the image portionto be decoded: acquiring one or more spatial motion informationpredictor candidates from one or more image portions in the image to bedecoded and one or more temporal motion information predictor candidatesfrom one or more image portions in an image different from the image tobe decoded; performing first processing on motion information predictorcandidates including the one or more spatial motion informationpredictor candidates but not including any temporal motion informationpredictor candidates for the image portion to be decoded, wherein thefirst processing comprises excluding a duplicate motion informationpredictor candidate; performing second processing on motion informationpredictor candidates including at least the one or more temporal motioninformation predictor candidates for the image portion to be decoded,wherein the second processing comprises excluding a duplicate motioninformation predictor candidate; obtaining, based on at least one ormore spatial motion information predictor candidates and one or moretemporal motion information predictor candidates resulting from thefirst and second processing, a set of motion information predictorcandidates for the motion information predictor.
 5. A method accordingto claim 4, wherein a motion information predictor candidate beingcapable of including a motion vector associated with a first indexcorresponding to a first reference picture list and a motion vectorassociated with a second index corresponding to a second referencepicture list, and wherein the method further comprises: generating oneor more additional motion information predictor candidates by combiningmotion vectors from first and second motion information predictorcandidates included in the set of motion information predictorcandidates, the motion vector from the first motion informationpredictor candidate being associated with the first index and the motionvector from the second motion information predictor candidate beingassociated with the second index; and including the generated one ormore additional motion information predictor candidates in the set ofmotion information predictor candidates.
 6. A method according to claim4, wherein, in a case where a motion information of an above imageportion of the image portion to be decoded is available, the one or morespatial motion information predictor candidates are able to include themotion information of the above image portion.
 7. A device fordetermining motion information predictor candidates for a motioninformation predictor for encoding an image portion in an image to beencoded by inter prediction, the device comprising: an acquiring unitconfigured to acquire one or more spatial motion information predictorcandidates from one or more image portions in the image to be encodedand one or more temporal motion information predictor candidates fromone or more image portions in an image different from the image to beencoded; a first processing unit configured to perform first processingon motion information predictor candidates including the one or morespatial motion information predictor candidates but not including anytemporal motion information predictor candidates for the image portionto be encoded, wherein the first processing comprises excluding aduplicate spatial motion information predictor candidate; a secondprocessing unit configured to perform second processing on motioninformation predictor candidates including at least the one or moretemporal motion information predictor candidates for the image portionto be encoded, wherein the second processing comprises excluding aduplicate motion information predictor candidate; an obtaining unitconfigured to obtain, based on at least one or more spatial motioninformation predictor candidates and one or more temporal motioninformation predictor candidates resulting from the first and secondprocessing, a set of motion information predictor candidates for themotion information predictor.
 8. A device according to claim 7, whereina motion information predictor candidate being capable of including amotion vector associated with a first index corresponding to a firstreference picture list and a motion vector associated with a secondindex corresponding to a second reference picture list, and wherein thedevice further comprises: a generating unit configured to generate oneor more additional motion information predictor candidates by combiningmotion vectors from first and second motion information predictorcandidates included in the set of motion information predictorcandidates, the motion vector from the first motion informationpredictor candidate being associated with the first index and the motionvector from the second motion information predictor candidate beingassociated with the second index; and an including unit configured toinclude the generated one or more additional motion informationpredictor candidates in the set of motion information predictorcandidates.
 9. A device according to claim 7, wherein, in a case where amotion information of an above image portion of the image portion to beencoded is available, the one or more spatial motion informationpredictor candidates are able to include the motion information of theabove image portion.
 10. A device for determining motion informationpredictor candidates for a motion information predictor for decoding ofan image portion in an image to be decoded by inter prediction, thedevice comprising: an acquiring unit configured to acquire one or morespatial motion information predictor candidates from one or more imageportions in the image to be decoded and one or more temporal motioninformation predictor candidates from one or more image portion in animage different from the image to be decoded; a first processing unitconfigured to perform first processing on motion information predictorcandidates including the one or more spatial motion informationpredictor candidates but not including any temporal motion informationpredictor candidates for the image portion to be decoded, wherein thepredetermined processing comprises excluding a duplicate motioninformation predictor candidate; a second processing unit configured toperform second processing on motion information predictor candidatesincluding at least the one or more temporal motion information predictorcandidates for the image portion to be decoded, wherein the secondprocessing comprises excluding a duplicate motion information predictorcandidate; an obtaining unit configured to obtain, based on at least oneor more spatial motion information predictor candidates and one or moretemporal motion information candidates resulting from the first andsecond processing, a set of motion information predictor candidates forthe motion information predictor.
 11. A device according to claim 10,wherein a motion information predictor candidate being capable ofincluding a motion vector associated with a first index corresponding toa first reference picture list and a motion vector associated with asecond index corresponding to a second reference picture list, andwherein the device further comprises: a generating unit configured togenerate one or more additional motion information predictor candidatesby combining motion vectors from first and second motion informationpredictor candidates included in the set of motion information predictorcandidates, the motion vector from the first motion informationpredictor candidate being associated with the first index and the motionvector from the second motion information predictor candidate beingassociated with the second index; and an including unit configured toinclude the generated one or more additional motion informationpredictor candidates in the set of motion information predictorcandidates.
 12. A device according to claim 10, wherein, in a case wherea motion information of an above image portion of the image portion tobe decoded is available, the one or more spatial motion informationpredictor candidates are able to include the motion information of theabove image portion.
 13. A non-transitory computer readable mediumcomprising processor executable code for a method of determining motioninformation predictor candidates for a motion information predictor forencoding an image portion in an image to be encoded by inter prediction,wherein execution of the processor executable code by one or moreprocessors causes the one or more processors to, for an image portion tobe encoded: acquire one or more spatial motion information predictorcandidates from one or more image portions in the image to be encodedand one or more temporal motion information predictor candidates fromone or more image portions in an image different from the image to beencoded; perform first processing on motion information predictorcandidates including the one or more spatial motion informationpredictor candidates but not including any temporal motion informationpredictor candidates for the image portion to be encoded, wherein thefirst processing comprises excluding a duplicate motion informationpredictor candidate; perform second processing on motion informationpredictor candidates including at least the one or more temporal motioninformation predictor candidates for the image portion to be encoded,wherein the second processing comprises excluding a duplicate motioninformation predictor candidate; obtain, based on at least one or morespatial motion information predictor candidates and one or more temporalmotion information predictor candidates resulting from the first andsecond processing, a set of motion information predictor candidates forthe motion information predictor.
 14. A non-transitory computer readablemedium comprising processor executable code for a method of determiningmotion information predictor candidates for a motion informationpredictor for decoding of an image portion in an image to be decoded byinter prediction, wherein execution of the processor executable code byone or more processors causes the one or more processors to, for animage portion to be decoded: acquire one or more spatial motioninformation predictor candidates from one or more image portions in theimage to be decoded and one or more temporal motion informationpredictor candidates from one or more image portions in an imagedifferent from the image to be decoded; perform first processing onmotion information predictor candidates including the one or morespatial motion information predictor candidates but not including anytemporal motion information predictor candidates for the image portionto be decoded, wherein the first processing comprises excluding aduplicate motion information predictor candidate; perform secondprocessing on motion information predictor candidates including at leastthe one or more temporal motion information predictor candidates for theimage portion to be decoded, wherein the second processing comprisesexcluding a duplicate motion information predictor candidate; obtain,based on at least one or more spatial motion information predictorcandidates and one or more temporal motion information predictorcandidates resulting from the first and second processing, a set ofmotion information predictor candidates for the motion informationpredictor.